Time-Varying Quadratic-Programming-Based Error Redefinition Neural Network Control and Its Application to Mobile Redundant Manipulators

By incorporating the redefined error monitor function into the network design, an error redefinition neural network (ERNN) is proposed to control mobile redundant manipulators to execute the tracking task in this article. The global asymptotic stability and the strong antidisturbance capability of t...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 67; no. 11; pp. 6151 - 6158
Main Authors Zheng, Lunan, Zhang, Zhijun
Format Journal Article
LanguageEnglish
Published New York IEEE 01.11.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Biological neural networks
Convergence
Convergence and robustness
Errors
Manipulators
mobile redundant manipulator (MRM)
motion planning control scheme
Network control
Network design
Neural networks
Quadratic programming
Recurrent neural networks
recurrent neural networks (RNNs)
Robustness
Task analysis
time-varying quadratic programming (TV-QP)
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Summary:By incorporating the redefined error monitor function into the network design, an error redefinition neural network (ERNN) is proposed to control mobile redundant manipulators to execute the tracking task in this article. The global asymptotic stability and the strong antidisturbance capability of the ERNN are proved theoretically. Furthermore, the ERNN can overcome the overshoot and constant disturbance. Meanwhile, the ERNN is input-to-state stable, while the bounded time-varying disturbance is considered as the control input.
Bibliography:ObjectType-Article-1
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2021.3128470